Sentence examples for minimizing prediction error from inspiring English sources

Irrespective of the smearing factor used, its value in minimizing prediction error depends crucially on the presence and nature of heteroskedasticity in the log scale residuals.

By minimizing prediction error in interacting with the environment, the net is forced to develop the conceptual resources to model the causal structure of the external world, and so navigate that world more effectively.

This refers to a computational framework for inferring the causes (intentions, goals, and motor commands) of sensory inputs (observed kinematics) by minimizing prediction error at all levels of a cortical hierarchy.

This forward projection drives the prediction units to provide a better prediction and thereby suppress the prediction error it receives; minimizing prediction error is the fundamental aim of the network.

Minimizing prediction error, in other words, was much bigger than it sounded.

In addition to minimizing prediction errors, the goal of network adaptation comprises also an optimization of the minimization rate such that new behaviors are favored over already learned ones, which would result in a vanishing improvement of predictability.

Thus, the comparison between two such sets can be used to derive a quantitative criterion in the hydrophobicity/complexity space by minimizing prediction errors.

In short, by minimizing prediction errors or surprise, the brain is trying to maximize the evidence for its generative model of the world.

We hold out a small number of individuals in the entire dataset as a validation set and select the value of the regularization parameter λ that gives the optimal level of sparsity, by minimizing prediction errors on the validation set.

Here we investigate whether systems that minimize prediction error e.g. predictive coding, can also show creativity, or on the contrary, prediction error minimization unqualifies for the design of systems that respond in creative ways to non-recurrent problems.

The brain attempts to minimize prediction error (the component of the input that is not predicted by the brain's current model).